What are the hardware requirements for CodeLlama 34B Hf?

CodeLlama 34B Hf requires approximately 67.5 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed CodeLlama 34B Hf and how large is it?

CodeLlama 34B Hf is developed by codellama, a model with 34b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does CodeLlama 34B Hf perform on standard benchmarks?

CodeLlama 34B Hf has the following published scores: MMLU 54.92, HumanEval (Python) 45.11. Compare against reference models on this page or on the LLM Explorer leaderboards.

CodeLlama 34B Hf by codellama — VRAM 67.5GB, 16K context

Name: CodeLlama 34B Hf
Author: codellama

CodeLlama 34B Hf is an open-source language model by codellama. Features: 34b LLM, VRAM: 67.5GB, Context: 16K, License: llama2, Code Generating, LLM Explorer Score: 0.13, Arc: 54.2, HellaSwag: 75.8, MMLU: 54.9, GSM8K: 34.3, HumanEval: 45.1.

Arxiv:2308.12950 Code Codegen Deploy:azure Endpoints compatible Llama Llama2 Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/codellama/CodeLlama-34b-hf

CodeLlama 34B Hf Benchmarks

ARC: 54.18 vs 96.7 (so35)^-44%

HellaSwag: 75.82 vs 95.3 (gpt4)^-20.4%

MMLU: 54.92 vs 88.3 (so35)^-37.8%

GSM8K: 34.34 vs 96.4 (so35)^-64.4%

HumanEvalA: 33.89

Python Eva: 45.11 vs 92 (so35)^-51%

Java Eval: 40.19

Javascript: 41.66

Racket Eva: 16.94

Rust Eval: 38.73

Swift Eval: 35.28

LLME Score: 0.13234

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

CodeLlama 34B Hf (codellama/CodeLlama-34b-hf)

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CodeLlama 34B Hf Parameters and Internals

Model Type

text generation, code generation

Use Cases

Areas:

Commercial, Research

Applications:

Code synthesis, Code understanding, Python language tasks

Primary Use Cases:

Code generation, Code understanding

Limitations:

Not tested in languages other than English

Supported Languages

English (proficient)

Training Details

Data Sources:

Same data as Llama 2

Methodology:

Optimized transformer architecture

Training Time:

January 2023 - July 2023

Hardware Used:

Meta’s Research Super Cluster

Model Architecture:

auto-regressive language model

Input Output

Input Format:

text

Accepted Modalities:

text

Output Format:

text

LLM Name	CodeLlama 34B Hf
Repository 🤗	https://huggingface.co/codellama/CodeLlama-34b-hf
Model Size	34b
Required VRAM	67.5 GB
Updated	2026-06-06
Maintainer	codellama
Model Type	llama
Model Files	9.8 GB: 1-of-7 9.7 GB: 2-of-7 9.7 GB: 3-of-7 9.7 GB: 4-of-7 9.7 GB: 5-of-7 9.7 GB: 6-of-7 9.2 GB: 7-of-7 9.8 GB: 1-of-7 9.7 GB: 2-of-7 9.7 GB: 3-of-7 9.7 GB: 4-of-7 9.7 GB: 5-of-7 9.7 GB: 6-of-7 9.4 GB: 7-of-7
Supported Languages	code
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.32.0.dev0
Tokenizer Class	CodeLlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the CodeLlama 34B Hf

Model	Likes	Downloads	VRAM
CodeLlama 34B Hf GGUF	3	747	12 GB
CodeLlama 34B GGUF	56	2779	14 GB
CodeLlama 34B AWQ	2	15	18 GB
CodeLlama 34B GPTQ	20	38	18 GB

Best Alternatives to CodeLlama 34B Hf

Best Alternatives	Context / RAM	Downloads	Likes
...gpt 32K Codellama 34B Instruct	32K / 67.5 GB	817	2
CodeLlama 34B Instruct Hf	16K / 67.5 GB	57493	304
CodeLlama 34B Instruct Hf	16K / 1.4 GB	23	3
ReflectionCoder CL 34B	16K / 67.6 GB	8336	0
Speechless Codellama 34B V2.0	16K / 67.5 GB	1073	17
Phind CodeLlama 34B V2	16K / 67.5 GB	1326	833
Phind CodeLlama 34B V1	16K / 67.5 GB	942	320
Phind CodeLlama 34B Python V1	16K / 67.5 GB	880	252
CodeLlama 34B Python Hf	16K / 67.5 GB	1096	99
CodeLlama 34B Hf	16K / 67.5 GB	1138	2

Note: green Score (e.g. "73.2") means that the model is better than codellama/CodeLlama-34b-hf.

Rank the CodeLlama 34B Hf Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Release v20260328a

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CodeLlama 34B Hf by codellama

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CodeLlama 34B Hf Benchmarks

CodeLlama 34B Hf Parameters and Internals

Quantized Models of the CodeLlama 34B Hf

Best Alternatives to CodeLlama 34B Hf

Rank the CodeLlama 34B Hf Capabilities

What open-source LLMs or SLMs are you in search of? 54415 in total.